From Reliability to Resilience: Planning the Grid Against the Extremes

Moreno, Rodrigo; Panteli, Mathaios; Mancarella, Pierluigi; Rudnick, H.; Lagos, Tomás; Navarro, A.; Ordóñez, Fernando; Araneda, Juan Carlos

doi:10.1109/mpe.2020.2985439

Cited by 66 publications

(38 citation statements)

References 5 publications

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“…Furthermore, the impact of other barely quantifiable or intangible factors (e.g., public perception, political influence, company reputation) may occasionally become dominant in final decisions, yet they are quite difficult to adequately account for. As a result, future challenges require new ways of thinking about the complex, interconnected and rapidly changing world [21,26,27,[29][30][31][32].…”

Section: Figurementioning

confidence: 99%

Global Methodology for Electrical Utilities Maintenance Assessment Based on Risk-Informed Decision Making

et al. 2021

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Modern electrical power utilities must deal with the replacement of large portions of their assets as they reach the end of their useful life. Their assets may also become obsolete due to technological changes or due to reaching their capacity limits. Major upgrades are also often necessary due to the need to grow capacity or because of the transition to more efficient and carbon-free power alternatives. Consequently, electrical power utilities are exposed to significant risks and uncertainties that have mostly external origins. In this context, an effective framework should be developed and implemented to maximize value from assets, ensure sustainable operations and deliver adequate customer service. Recent developments show that combining the concepts of asset management and resilience offers strong potential for such a framework—not only for electrical utilities, but for industry, too. Given that the quality and continuity of service are critical factors, the concept of Value of Lost Load (VoLL) is an important indicator for assessing the value of undelivered electrical energy due to planned or unplanned outages. This paper presents a novel approach for integrating the power grid reliability simulator into a holistic framework for asset management and electrical power utility resilience. The proposed approach provides a sound foundation for Risk-Informed Decision Making in asset management. Among other things, it considers asset performance as well as the impact of both current grid topology and customer profiles on grid reliability and VoLL. A case study on a major North American electrical power utility demonstrates the applicability of the proposed methodology in assessing maintenance strategy.

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Section: Figurementioning

confidence: 99%

Global Methodology for Electrical Utilities Maintenance Assessment Based on Risk-Informed Decision Making

et al. 2021

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“…Espinoza, Panteli and others [16] took this framework a step further to test different strategies to make the power system more robust and responsive, using an example of Great Britain. Moreno, Panteli and others [17] more recently have further reiterated the need for planning models to make the transition from a relatively simple and one-dimensional reliability criterion to multi-dimensional resilience standards. There have also been case studies that incorporate resilience considerations in practical systems including flooding risks in Bangladesh [10], impact of storms on the British transmission network [18] and impact of cyclones on household level supply in Florida [19].…”

Section: A An Overview Of the Literaturementioning

confidence: 99%

“…One area where better translation and integration of resilience metrics into planning is needed, relates to the difference between reliability and resilience [17]. Resilience and reliability are two closely related concepts used to determine a power system's performance during an outage.…”

Section: A Resilience Vs Reliabilitymentioning

confidence: 99%

“…Figure 1 shows different phases of a system following a disaster including the response, recovery and transition phase until normal operation is restored. Resilience focuses on all of these phases [15][16][17][18][19]33] including the initial depth of the outage, what back-up measures are in place to sustain critical operation/load, what responses can be taken to restore supply, etc. Resilience is about the entire process and how the system should be designed to render it reliable.…”

Section: A Resilience Vs Reliabilitymentioning

confidence: 99%

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Planning for a Resilient Home Electricity Supply System

2021

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Resilience of power systems is already a key issue that is getting frequent attention all over the world. It is useful to analyze resilience issues not only for bulk supply, but at all levels including at a customer level. This is because distributed energy resources can play a prominent role in enhancing resilience. Although the literature on planning models, tools and data for bulk supply and distribution systems have expanded in recent years, customer-centric planning, e.g., for an individual household, is yet to receive adequate attention. Although solar PV and battery storage at a household level have been analyzed, how these resources can be optimally combined, together with grid supply, from a resilience perspective is the focus of this study. The study demonstrates how a conceptual framework can be developed to show the trade-off between system costs and resilience including its dimensions such as duration, depth and frequency of service outages. A planning model is developed that incorporates multiple facets of resilience and individual customer preferences. The model considers power system resilience explicitly as a constraint. The model is implemented for a household level case study in Miami, Florida. The results show there are complex tradeoffs among different dimensions of resilience. The study demonstrates how combined resilience metrics can be formulated and evaluated using the proposed least-cost planning model at a household level to optimize grid supply together with solar, battery storage and diesel generators. The model allows a planner to directly embed a resilience standard to drive the optimal supply mix. These concepts and the modeling construct can also be applied at other levels of planning, including community level and bulk supply system planning.

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“…Quantile regression is widely used for probabilistic forecasting as it makes no assumptions about the shape of predictive distributions, but is not well suited to estimating conditional extremes as data is increasingly sparse in the tails, so special treatment is required. While there are well established practices modelling extreme events for planning purposes [11], such heat waves, the extremes of short-term forecast errors and uncertainty have received little attention. Panteli et al discuss the importance of short-term forecasts of extremes in power system resilience in [12] and highlighted this as an area where development of advanced tools is required.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Forecasting of Regional Net-Load With Conditional Extremes and Gridded NWP

Browell

Fasiolo

2021

IEEE Trans. Smart Grid

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The increasing penetration of embedded renewables makes forecasting net-load, consumption less embedded generation, a significant and growing challenge. Here a framework for producing probabilistic forecasts of net-load is proposed with particular attention given to the tails of predictive distributions, which are required for managing risk associated with lowprobability events. Only small volumes of data are available in the tails, by definition, so estimation of predictive models and forecast evaluation requires special attention. We propose a solution based on a best-in-class load forecasting methodology adapted for netload, and model the tails of predictive distributions with the Generalised Pareto Distribution, allowing its parameters to vary smoothly as functions of covariates. The resulting forecasts are shown to be calibrated and sharper than those produced with unconditional tail distributions. In a use-case inspired evaluation exercise based on reserve setting, the conditional tails are shown to reduce the overall volume of reserve required to manage a given risk. Furthermore, they identify periods of high risk not captured by other methods. The proposed method therefore enables user to both reduce costs and avoid excess risk.

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From Reliability to Resilience: Planning the Grid Against the Extremes

Cited by 66 publications

References 5 publications

Global Methodology for Electrical Utilities Maintenance Assessment Based on Risk-Informed Decision Making

Global Methodology for Electrical Utilities Maintenance Assessment Based on Risk-Informed Decision Making

Planning for a Resilient Home Electricity Supply System

Probabilistic Forecasting of Regional Net-Load With Conditional Extremes and Gridded NWP

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